Abstract
This paper presents a systematic approach to evaluate the tracking performance limits for different sensor modalities (lidar, radar and vision) and for combination of these sensors modalities. The Cramer-Rao lower bound (CRLB) is used to predict the tracking performance limits for state of the art sensors such as the Continental ARS408 radar, Velodyne HDL-64E lidar and a state of the art monocular/stereo camera. The performance is evaluated by computing the theoretical CRLB in urban and highway environments. In both scenarios, the best performance was achieved by a combination of lidar and radar. In the close range, stereo vision improves the longitudinal tracking performance limits. Furthermore, radar is crucial on highways because of the quick longitudinal convergence characteristics.
Original language | English |
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Title of host publication | Proceedings of the 20th International Conference on Information Fusion |
Place of Publication | Piscataway, NJ, USA |
Publisher | IEEE |
Number of pages | 8 |
ISBN (Print) | 978-0-9964-5270-0 |
DOIs | |
Publication status | Published - 2017 |
Event | 20th International Conference on Information Fusion - Xi'an, China Duration: 10 Jul 2017 → 13 Jul 2017 |
Conference
Conference | 20th International Conference on Information Fusion |
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Country/Territory | China |
City | Xi'an |
Period | 10/07/17 → 13/07/17 |
Keywords
- Radar tracking
- Laser radar
- Covariance matrices
- Cameras
- Automobiles
- Measurement uncertainty